In machine learning, what does the term "training data" refer to?

The term "training data" specifically refers to the dataset used to build and improve a machine learning model. This data contains input features along with their corresponding output labels (in supervised learning) and is utilized by algorithms to learn the underlying patterns and relationships within the data. By processing training data, the model adjusts its parameters to make more accurate predictions or classifications based on the input it receives.

By using a well-structured training dataset, a model can generalize better when it is presented with new, unseen data. The goal is for the model to learn from the training data so that it can perform accurately on tasks beyond just the examples it has encountered during training.